Tech Briefs

Software for Acquiring Image Data for PIV

PIV Acquisition (PIVACQ) is a computer program for acquisition of data for particle- image velocimetry (PIV). In the PIV system for which PIVACQ was developed, small particles entrained in a flow are illuminated with a sheet of light from a pulsed laser. The illuminated region is monitored by a charge-coupleddevice camera that operates in conjunction with a data-acquisition system that includes a frame grabber and a countertimer board, both installed in a single computer. The camera operates in “framestraddle” mode where a pair of images can be obtained closely spaced in time (on the order of microseconds). The frame grabber acquires image data from the camera and stores the data in the computer memory. The counter/timer board triggers the camera and synchronizes the pulsing of the laser with acquisition of data from the camera. PIVPROC coordinates all of these functions and provides a graphical user interface, through which the user can control the PIV data-acquisition system. PIVACQ enables the user to acquire a sequence of single-exposure images, display the images, process the images, and then save the images to the computer hard drive. PIVACQ works in conjunction with the PIVPROC program — described in prior NASA Tech Briefs articles — which processes the images of particles into the velocity field in the illuminated plane.

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Detecting Edges in Images by Use of Fuzzy Reasoning

Human visual processing is partly imitated in order to harness some of its power. A method of processing digital image data to detect edges includes the use of fuzzy reasoning. The method is completely adaptive and does not require any advance knowledge of an image.

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Program for User-Friendly Management of Input and Output Data Sets

A computer program manages large, hierarchical sets of input and output (I/O) parameters (typically, sequences of alpha- numeric data) involved in computational simulations in a variety of technological disciplines. This program represents sets of parameters as structures coded in object-oriented but otherwise standard American National Standards Institute C language. Each structure contains a group of I/O parameters that “make sense” as a unit in the simulation program with which this program is used. The addition of options and/or elements to sets of parameters amounts to the addition of new elements to data structures. By association of child data generated in response to a particular user input, a hierarchical ordering of input parameters can be achieved. Associated with child data structures are the creation and description mechanisms within the parent data structures. Child data structures can spawn further child data structures. In this program, the creation and representation of a sequence of data structures is effected by one line of code that looks for children of a sequence of structures until there are no more children to be found. A linked list of structures is created dynamically and is completely represented in the data structures themselves. Such hierarchical data presentation can guide users through otherwise complex setup procedures and it can be integrated within a variety of graphical representations.

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Numerical Modeling of Nanoelectronic Devices

Nanoelectronic Modeling 3-D (NEMO 3-D) is a computer program for numerical modeling of the electronic structure properties of a semiconductor device that is embodied in a crystal containing as many as 16 million atoms in an arbitrary configuration and that has overall dimensions of the order of tens of nanometers. The underlying mathematical model represents the quantum-mechanical behavior of the device resolved to the atomistic level of granularity. The system of electrons in the device is represented by a sparse Hamiltonian matrix that contains hundreds of millions of terms. NEMO 3-D solves the matrix equation on a Beowulf-class cluster computer, by use of a parallel-processing matrix×vector multiplication algorithm coupled to a Lanczos and/or Rayleigh-Ritz algorithm that solves for eigenvalues. In a recent update of NEMO 3-D, a new strain treatment, parameterized for bulk material properties of GaAs and InAs, was developed for two tight-binding submodels. The utility of the NEMO 3-D was demonstrated in an atomistic analysis of the effects of disorder in alloys and, in particular, in bulk InxGal–xAs and in In0.6Ga0.4As quantum dots.

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Noncoherent Tracking of a Source of a Data-Modulated Signal

Properties of the modulation would be exploited to determine direction-dependent phase differences. A proposed tracking receiver system containing three suitably positioned antenna elements and special signal-processing equipment would determine the direction of incidence of a microwave signal containing spread- spectrum digital data modulation. If the system were to contain two sets of antenna elements separated by a known baseline, it could determine the location of the transmitter as the intersection of the lines of incidence on the two antennas. Such systems could be used for diverse purposes in outer space and on Earth, including tracking astronauts and small robotic spacecraft working outside a spacecraft or space station, and locating cellular telephones from which distress calls have been made. The principle of operation does not require the transmission of a special identifying or distress signal by the cellular telephone or other transmitter to be tracked; instead, the system could utilize the data signal routinely sent by the transmitter, provided that the signal had the characteristics needed for processing as described below.

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Quad-Tree Visual-Calculus Analysis of Satellite Coverage

The computational burden is less than in a pixel representation. An improved method of analysis of coverage of areas of the Earth by a constellation of radio-communication or scientific-observation satellites has been developed. This method is intended to supplant an older method in which the global-coverage- analysis problem is solved from a ground-to-satellite perspective. The older method is suitable for coarse-grained analysis of coverage of a constellation of a few satellites, but the algorithms of the older method are too slow and cumbersome for the large scope of the problem of analysis of coverage of a modern constellation of many satellites intended to provide global coverage all the time. In contrast, the present method provides for rapid and efficient analysis. This method is derived from a satellite-to-ground perspective and involves a unique combination of two techniques for multiresolution representation of map features on the surface of a sphere.

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Update on EMD and Hilbert-Spectra Analysis of Time Series

U.S. Patent 6,381,559 presents further information about the method described in "Analyzing Time Series Using EMD and Hilbert Spectra" (GSC-13817), NASA Tech Briefs, Vol. 24, No. 10 (October 2000), page 63. To recapitulate: The method is especially well suited for analyzing time-series data that represent nonstationary and nonlinear physical phenomena. The method is based principally on the concept of empirical mode decomposition (EMD), according to which any complicated signal (as represented by digital samples) can be decomposed into a finite number of functions, called "intrinsic mode functions" (IMFs), that admit well-behaved Hilbert transforms. The local energies and the instantaneous frequencies derived from the IMFs through Hilbert transforms can be used to construct an energy-frequency-time distribution, denoted a Hilbert spectrum. The patent expands on the description in the cited prior article by explaining underlying mathematical principles and describing details of implementation. The patent also describes, as major elements of the method, the options of (1) filtering the original signal by combining a subset of IMFs and (2) fitting a curve to the filtered signal — something that it may not be possible to do with the original signal.

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